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Liquid cooling technology for semiconductor chips is 10 times more efficient than previous record

AI data centers are power-hungry. Not only do artificial intelligence computations consume enormous amounts of electricity, but a significant amount of energy is also required to cool the semiconductor chips that heat up during operation. As AI chips continue to deliver higher performance, the amount of heat they generate increases rapidly. As a result, conventional air cooling and external copper heat spreaders are approaching their practical limits. To address this challenge, a KAIST research team has developed an ultra-high-efficiency liquid-cooling technology that cools semiconductor chips from within.

A joint research team led by Professor Sung Jin Kim of the Department of Mechanical Engineering and Professor Ikjin Lee of the School of AI and Computing has developed a highly efficient liquid-cooling technology that directly cools high-heat-flux semiconductor chips using room-temperature water. The researchers achieved this by embedding liquid-cooling channels, thinner than a human hair, directly inside a silicon semiconductor chip. The paper is published in the journal Energy Conversion and Management.

The team successfully maintained the chip temperature below 100° C (212° F) even under extreme heat-generation conditions exceeding 2,000 watts per square centimeter (W/cm2).

Passive quantum error correction doubles qubit lifetime, reaching break-even point

A team of U.S. researchers has designed a passive quantum error correction technique that enables qubits to correct their own errors. Demonstrated by Shruti Shirol and colleagues at the University of Massachusetts Amherst, the protocol transforms the inevitable dissipation of energy in qubit systems from a hindrance into an advantage, offering a promising route toward practical quantum computing outside the lab. The research has been published in Physical Review X.

As the building blocks of quantum computers, qubits aren’t limited to being either a 0 or a 1, like the classical bits that computers use today. Instead, they can exist in quantum superpositions of these states, offering new ways of storing and processing information.

However, these states are notoriously fragile. As they interact with vibrations and impurities in their surroundings, they can easily be destroyed, resulting in energy being dissipated from the system. To date, this poses one of the biggest roadblocks to building quantum computers in realistic settings outside the lab.

Clinician–scientists identify brain network linked to deadliest childhood brain cancer

A human brain network associated with survival in children with diffuse midline glioma (DMG), the deadliest childhood brain cancer, has been identified by UCL clinician-scientists, raising the possibility of entirely new treatment approaches. The researchers found that DMG tumors seem to exploit the brain’s existing neural circuitry to drive tumor growth and progression. Tumors that were more strongly connected to this network were associated with significantly shorter patient survival.

The study, published in Nature, builds on pioneering work in the field of cancer neuroscience, which shows that brain tumors, including DMG, dynamically interact with the otherwise healthy brain.

The study was led by Dr. Jai Sidpra and Dr. Valentina Lind, medical students enrolled in the MBPhD Program within the UCL Division of Medicine and senior author Professor Darren Hargrave’s group at the UCL Great Ormond Street Institute of Child Health.

Beyond frozen snapshots, protein ‘breathing’ comes into view with combined imaging methods

Advances in structural biology have allowed scientists to determine molecular structures with atomic-level detail, sometimes yielding static snapshots that do not reflect the dynamism of proteins. However, these motions are often crucial for biological function. Researchers from the Institute of Science and Technology Austria (ISTA), together with international collaborators, have now combined several methods to shed light on how proteins “breathe” and how some experimental techniques freeze their motion. The findings—which could boost protein design approaches and improve AI-based structural prediction tools—are published in Nature Chemistry.

Despite serving as structural biology’s central pillar for more than half a century, protein crystallography has yielded static molecular structures—like still frames from a video—far from the buzzing life inside cells.

“How much can these ‘frozen snapshots’ of protein structures really tell us about their true biological functions and bustling molecular environments?” asks Lea Becker, the study’s first author and a Ph.D. student in Professor Paul Schanda’s group at the Institute of Science and Technology Austria (ISTA).

Quasi-1D material unlocks electric control of charge waves beyond standard limits

The ability to control the movement of negatively charged particles (i.e., electrons) is central to the functioning of all modern electronic devices. This control is typically attained using a gate, an electrode via which an applied electric field alters a material’s electrical properties.

In many electronic devices, the effectiveness of electrical gating depends on a device’s capacitance (i.e., a measure of how much electric charge can be induced or stored for a given voltage). Recently, however, electronics engineers have been exploring the potential of new materials that exhibit unusual collective electron behaviors, which could be leveraged to surpass the gating performance of contemporary electronics.

Researchers at University of California, Los Angeles (UCLA) and University of California, Riverside (UCR) recently demonstrated the potential of a new quasi-one-dimensional (1D) quantum material, showing that it can dramatically enhance the electrical control of collective electronic states known as charge density waves (CDWs).

Tiny chip could help cameras spot hidden details

A tiny new chip could give cameras and sensing systems a far sharper view of the world, helping them detect subtle differences in materials and environments that standard color imaging systems cannot see.

In research led by Zhejiang University in collaboration with RMIT University, scientists have demonstrated a new way to build light-analysis capability directly into imaging hardware.

Cameras are highly effective at capturing images, but applications such as machine vision, automated inspection and environmental monitoring depend on understanding different colors and wavelengths of light, not just what something looks like. That information can reveal differences in materials, surface conditions or environmental changes that appear identical to the human eye.

Most precise measurement of the force that binds nuclear matter achieved

Trinity’s Prof. Stefan Sint, along with collaborators from Germany, Spain and Italy, has published the most precise determination to date of the strong coupling constant. This parameter governs the interactions between quarks and gluons, the fundamental components of nuclear matter. The new result halves the error of all previous experimental measurements combined, setting a new benchmark for the Standard Model, which summarizes our current knowledge of elementary particle physics.

This advance will improve our understanding of how quarks and gluons behave inside protons and enable high-precision measurements of the Higgs boson and its properties. More generally, improved quantitative control of the strong interactions increases the likelihood of discovering effects of yet unknown physics at CERN’s Large Hadron Collider (LHC).

Prof. Sint from Trinity’s School of Mathematics was one of the researchers whose landmark results were published in Nature.

Ultrafast laser pulses reveal a material’s hidden state of matter

What would it take to instantly transform a material from an electrical insulator into a conductive state without ever touching it? Using ultrafast laser pulses and powerful X-rays, scientists at the National Synchrotron Light Source II (NSLS-II)—a U.S. Department of Energy (DOE) Office of Science user facility at DOE’s Brookhaven National Laboratory—developed a methodology to generate “hidden” phases and understand why they work.

This research not only reveals a hidden state of matter and its fundamental interactions but also points toward new ways to control materials for future electronics and quantum technologies. Their work was recently published in Physical Review X.

At the heart of the research is an interesting class of quantum materials called magnetoresistive manganites. Under the right conditions, their properties and behaviors can change completely with external stimuli. In this case, the team used short bursts of laser light lasting 100 femtoseconds (one hundred quadrillionths of a second) to “switch” a material from an insulating state, where electricity cannot flow, to a conductive one.

Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan Ozcan, introduced a snapshot 3D image projection system that integrates a digital encoder with a passive diffractive optical decoder, jointly optimized end-to-end through deep learning. The hybrid architecture projects multiple distinct images onto closely spaced axial planes in a single shot, marking a significant step toward compact, high-fidelity volumetric display technologies. The research is published in the journal Light: Science & Applications.

3D image display technology is essential for next-generation holography, immersive visualization, and augmented and virtual reality (AR/VR) interfaces, where accurate focal cues across depth are critical for natural depth perception and visual comfort. However, dense depth multiplexing in conventional holographic displays remains a challenge: As the axial image planes approach one another in the output volume, diffraction-induced crosstalk rapidly degrades depth selectivity and image fidelity.

Supercomputer illuminates subatomic particle that helps hold matter together

A team of researchers has leveraged a supercomputer at the U.S. Department of Energy’s (DOE) Argonne National Laboratory to reveal the internal structure of a pion in unprecedented detail. The findings are published in the Journal of High Energy Physics.

Pions are subatomic particles that help bind matter at some of the smallest scales in nature. They are closely connected to the strong nuclear force, the fundamental force that holds protons and neutrons together inside atomic nuclei. Understanding how pions work can help scientists explain how matter forms at its most fundamental level.

“Pions mediate the strong force that binds nucleons—that is, the protons and neutrons that account for an atom’s mass,” said Yong Zhao, an Argonne physicist and principal investigator on the project.

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